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Fundamental Frequency Optimization of Laminated Cylindrical Panels by Elitist-Genetic Algorithm
In this paper, fundamental frequency optimization of symmetrically laminated cylindrical panels is investigated by the Elitist-Genetic algorithm (E-GA). The number of layers, the fiber orientation angles, edge conditions, length/width (a/b) and length/R (a/R) ratios are considered as design variables. The classical shallow shell theory (Donnell’s formulation) is applied to calculate the natural frequencies of laminated cylindrical curved panels. To improve the speed of the optimization process, the elitist strategy is used in the Genetic algorithm and the fitness function is computed with a semi-analytical finite strip method (FSM). A program based on Maple is used for this purpose. To check the validity, the obtained results are also compared with some other stacking sequences.
Fundamental Frequency Optimization of Laminated Cylindrical Panels by Elitist-Genetic Algorithm
In this paper, fundamental frequency optimization of symmetrically laminated cylindrical panels is investigated by the Elitist-Genetic algorithm (E-GA). The number of layers, the fiber orientation angles, edge conditions, length/width (a/b) and length/R (a/R) ratios are considered as design variables. The classical shallow shell theory (Donnell’s formulation) is applied to calculate the natural frequencies of laminated cylindrical curved panels. To improve the speed of the optimization process, the elitist strategy is used in the Genetic algorithm and the fitness function is computed with a semi-analytical finite strip method (FSM). A program based on Maple is used for this purpose. To check the validity, the obtained results are also compared with some other stacking sequences.
Fundamental Frequency Optimization of Laminated Cylindrical Panels by Elitist-Genetic Algorithm
Sadr-Lahidjani, Mohammad Homayoun (author) / Bargh, Hadi Ghashochi (author)
2011
6 Seiten
Conference paper
English
Fundamental Frequency Optimization of Laminated Cylindrical Panels by Elitist-Genetic Algorithm
British Library Online Contents | 2011
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